Electricity Market Module
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Electricity Market Module

The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is 

composed of four submodules— electricity load and demand, electricity capacity planning, electricity fuel dispatching, and 

electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed 

description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 

2014, DOE/EIA-M068(2014).

Based on fuel prices and electricity demands provided by the other modules of NEMS, the EMM determines the most 

economical way to supply electricity, within environmental and operational constraints. There are assumptions about the 

operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes 

the model parameters and assumptions used in the EMM. It includes a discussion of legislation and regulations that are 

incorporated in the EMM, as well as information about the climate change action plan. The various electricity side cases are also 

described.

EMM regions 

The supply regions used in the EMM are based on the North American Electric Reliability Corporation regions and subregions 

shown in Figure 6.

Figure 6. Electricity Market Model Supply Regions

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Electricity Market Module

Model parameters and assumptions 

Generating capacity types 

The capacity types represented in the EMM are shown in Table 8.1.

Table 8.1. Generating capacity types represented in the Electricity Market Module

Capacity Type

Existing coal steam plants1

High Sulfur Pulverized Coal with Wet Flue Gas Desulfurization

Advanced Coal - Integrated Coal Gasification Combined Cycle (IGCC)

IGCC with Carbon Sequestration

Oil/Gas Steam - Oil/Gas Steam Turbine

Combined Cycle - Conventional Gas/Oil Combined Cycle Combustion Turbine

Advanced Combined Cycle - Advanced Gas/Oil Combined Cycle Combustion Turbine

Advanced Combined Cycle with carbon sequestration

Combustion Turbine - Conventional Combustion Turbine

Advanced Combustion Turbine - Steam Injected Gas Turbine

Molten Carbonate Fuel Cell

Conventional Nuclear

Advanced Nuclear - Advanced Light Water Reactor

Generic Distributed Generation - Baseload

Generic Distributed Generation - Peak

Conventional Hydropower - Hydraulic Turbine

Pumped Storage - Hydraulic Turbine Reversible

Geothermal

Municipal Solid Waste

Biomass - Fluidized Bed

Solar Thermal - Central Tower

Solar Photovoltaic - Fixed Tilt

Wind

Wind Offshore

1

The EMM represents 32 different types of existing coal steam plants, based on the different possible configuration of NOx, particulate and SO2

emission control devices, as well as future options for controlling mercury and carbon.

Source: U.S. Energy Information Administration.

New generating plant characteristics 

The cost and performance characteristics of new generating technologies are inputs to the electricity capacity planning 

submodule (Table 8.2). These characteristics are used in combination with fuel prices from the NEMS fuel supply modules and 

foresight on fuel prices, to compare options when new capacity is needed. Heat rates for new fossil-fueled technologies are 

assumed to decline linearly through 2025.

For AEO2013, EIA commissioned an external consultant to update current cost estimates for utility-scale electric generating 

plants [1]. This report used a consistent methodology, similar to the one used to develop the estimates for AEO2011 and 

AEO2012, but accounted for more recent data and experience. Because the costs from the report were assumed to be consistent 

with plants that would be ordered in 2012, for AEO2014 the initial costs were adjusted to account for learning from capacity built 

during 2012. A cost adjustment factor, based on the producer price index for metals and metal products, allows the overnight 

costs to fall in the future if this index drops, or rise further if it increases.

The overnight costs shown in Table 8.2 represent the estimated cost of building a plant in a typical region of the country. 

Differences in plant costs due to regional distinctions are calculated by applying regional multipliers. Regional multipliers by 

technology are also based on regional cost estimates developed by the consultant. The regional variations account for multiple 

96 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2014
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Table 8.2. Cost and performance characteristics of new central station electricity generating technologies

Technology

Online

Year1

Size

(MW)

Lead 

time

(years)

Base 

Overnight 

Cost in 

2013

(2012 $/kW)

Contingency Factors

Total 

Overnight

Cost in 20134

(2012 $/kW)

Variable

O&M5

(2012 $/

mWh)

Fixed

O&M

(2012$/

kW/yr.)

Heatrate6

in 2013

(Btu/

kWh)

nth-ofa-kind 

Heatrate 

(Btu/

kWh

Project 

Contingency

Factor2

Technological

Optimism

Factor3

Scrubbed Coal New 2017 1300 4 2,734 1.07 1.00 2,925 4.47 31.18 8,800 8,740

Integrated CoalGasification Comb 

Cycle (IGCC) 2017 1200 4 3,525 1.07 1.00 3,771 7.22 51.39 8,700 7,450

IGCC with Carbon 

sequestion 2017 520 4 5,958 1.07 1.03 6,567 8.45 72.84 10,700 8,307

Conv Gas/Oil Comb 

Cycle 2016 620 3 871 1.05 1.00 915 3.60 13.17 7,050 6,800

Adv Gas/Oil Comb 

Cycle (CC) 2016 400 3 945 1.08 1.00 1,021 3.27 15.37 6,430 6,333

Adv CC with carbon 

sequestration 2017 340 3 1,856 1.08 1.04 2,084 6.78 31.79 7,525 7,493

Conv Comb Turbine8 2015 85 2 924 1.05 1.00 971 15.45 7.34 10,817 10,450

Adv Comb Turbine 2015 210 2 641 1.05 1.00 673 10.37 7.04 9,750 8,550

Fuel Cells 2016 10 3 6,099 1.05 1.10 7,044 42.99 0.00 9,500 6,960

Adv Nuclear 2019 2234 6 4,763 1.10 1.05 5,501 2.14 93.28 10,464 10,464

Distributed 

Generation - Base 2016 2 3 1,414 1.05 1.00 1,485 7.76 17.45 9,027 8,900

Distributed 

Generation - Peak 2015 1 2 1,698 1.05 1.00 1,783 7.76 17.45 10,029 9,880

Biomass 2017 50 4 3,590 1.07 1.02 3,919 5.26 105.64 13,500 13,500

Geothermal7,9 2016 50 4 2,375 1.05 1.00 2,494 0.00 112.92 9,716 9,716

Muncipal Solid Waste 2014 50 3 7,751 1.07 1.00 8,294 8.75 392.81 18,000 18,000

Conventional 

Hydropower9 2017 500 4 2,213 1.10 1.00 2,435 2.65 14.83 9,716 9,716

Wind 2014 100 3 2,061 1.07 1.00 2,205 0.00 39.55 9,716 9,716

Wind Offshore 2017 400 4 4,503 1.10 1.25 6,192 0.00 74.00 9,716 9,716

Solar Thermal7 2016 100 3 4,715 1.07 1.00 5,045 0.00 67.26 9,716 9,716

Photovoltaic7,10 2015 150 2 3,394 1.05 1.00 3,564 0.00 24.69 9,716 9,716 1 Online year represents the first year that a new unit could be completed, given an order date of 2013. For wind, geothermal and landfill gas, the online year was 

moved earlier to acknowledge both market activity already occurring as well as the incentive for certain types of projects to develop at an accelerated rate in order 

to qualify for the Production Tax Credit. 

2

A contingency allowance is defined by the American Association of Cost Engineers as the “specific provision for unforeseeable elements of costs within a defined 

project scope; particularly important where previous experience has shown that unforeseeable events which will increase costs are likely to occur.”

3

The technological optimism factor is applied to the first four units of a new, unproven design; it reflects the demonstrated tendency to underestimate actual costs 

for a first-of-a-kind unit.

4Overnight capital cost including contingency factors, excluding regional multipliers and learning effects. Interest charges are also excluded. These represent costs 

of new projects initiated in 2013. 

5

O&M = Operations and maintenance.

6

For hydro, wind, solar and geothermal technologies, the heatrate shown represents the average heatrate for conventional thermal generation as of 2012.  This 

is used for purposes of calculating primary energy consumption displaced for these resources, and does not imply an estimate of their actual energy conversion 

efficiency.

7

Capital costs are shown before investment tax credits are applied. 

8

Combustion turbine units can be built by the model prior to 2015 if necessary to meet a given region’s reserve margin.

9

Because geothermal and hydro cost and performance characteristics are specific for each site, the table entries represent the cost of the least expensive plant 

that could be built in the Northwest Power Pool region, where most of the proposed sites are located.

10Costs and capacities are expressed in terms of net AC power available to the grid for the installed capacity. 

Sources: For the AEO2014 cycle, EIA continues to use the previously developed cost estimates for utility-scale electric generating plants, updated by external 

consultants for AEO2013. This report can be found at http://www.eia.gov/forecasts/capitalcost/. The costs were assumed to be consistent with plants that would 

be ordered in 2012, and learning from capacity built in 2012 has been applied in the initial costs above. Site-specific costs for geothermal were provided by the 

National Renewable Energy Laboratory, “Updated U.S. Geothermal Supply Curve,” February 2010.

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Electricity Market Module

factors, such as differences in terrain, weather, population, and labor wages. The base overnight cost is multiplied by a 

project contingency factor and a technological optimism factor (described later in this chapter), resulting in the total 

construction cost for the first-of-a-kind unit used for the capacity choice decision.

Technological optimism and learning 

Overnight costs for each technology are calculated as a function of regional construction parameters, project contingency, 

and technological optimism and learning factors.

The technological optimism factor represents the demonstrated tendency to underestimate actual costs for a first-of-akind, unproven technology. As experience is gained (after building four units) the technological optimism factor is gradually 

reduced to 1.0.

The learning function in NEMS is determined at a component level. Each new technology is broken into its major 

components, and each component is identified as revolutionary, evolutionary or mature. Different learning rates 

are assumed for each component, based on the level of experience with the design component (Table 8.3). Where 

technologies use similar components, these components learn at the same rate as these units are built. For example, it is 

assumed that the underlying turbine generator for a combustion turbine, combined cycle and integrated coal-gasification 

combined cycle unit is basically the same. Therefore construction of any of these technologies would contribute to learning 

reductions for the turbine component.

The learning function, OC, has the nonlinear form:

 OC(C) = a*C-b,

where C is the cumulative capacity for the technology component.

Table 8.3. Learning parameters for new generating technology components

Technology Component

Period 1

Learning Rate 

(LR1)

Period 2

Learning Rate 

(LR2)

Period 3

Learning Rate 

(LR3)

Period 1

Doublings

Period 2

Doublings

Minimum Total

Learning by 2035

Pulverized Coal - - 1% - - 5%

Combustion Turbine - conventional - - 1% - - 5%

Combustion Turbine - advanced - 10% 1% - 5 10%

HRSG1 - - 1% - - 5%

Gasifier - 10% 1% - 5 10%

Carbon Capture/Sequestration 20% 10% 1% 3 5 20%

Balance of Plant - IGCC - - 1% - - 5%

Balance of Plant - Turbine - - 1% - - 5%

Balance of Plant - Combined Cycle - - 1% - - 5%

Fuel Cell 20% 10% 1% 3 5 20%

Advanced Nuclear 5% 3% 1% 3 5 10%

Fuel prep - Biomass - 10% 1% - 5 10%

Distributed Generation - Base - 5% 1% - 5 10%

Distributed Generation - Peak - 5% 1% - 5 10%

Geothermal - 8% 1% - 5 10%

Municipal Solid Waste - - 1% - - 5%

Hydropower - - 1% - - 5%

Wind - - 1% - - 5%

Wind Offshore 20% 10% 1% 3 5 20%

Solar Thermal 20% 10% 1% 3 5 10%

Solar PV - Module - 10% 1% - 5 10%

Balance of Plant - Solar PV - 10% 1% - 5 10%

1

HRSG = Heat Recovery Steam Generator

Note: Please see the text for a description of the methodology for learning in the Electricity Market Module.

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis.

The progress ratio (pr) is defined by speed of learning (e.g., how much costs decline for every doubling of capacity). 

The reduction in capital cost for every doubling of cumulative capacity (LR) is an exogenous parameter input for each 

component (Table 8.3). The progress ratio and LR are related by:

 pr = 2-b = (1 - LR)

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The parameter “b” is calculated from the second equality above (b =-(ln(1-LR)/ln(2))). The parameter “a” is computed from 

initial conditions, i.e.

 a =OC(C0)/Co -b

where C0 is the initial cumulative capacity. Once the rates of learning (LR) and the cumulative capacity (C0) are known for 

each interval, the parameters (a and b) can be computed. Three learning steps were developed to reflect different stages of 

learning as a new design is introduced into the market. New designs with a significant amount of untested technology will see 

high rates of learning initially, while more conventional designs will not have as much learning potential. Costs of all design 

components are adjusted to reflect a minimal amount of learning, even if new capacity additions are not projected. This 

represents cost reductions due to future international development or increased research and development.

Once the learning rates by component are calculated, a weighted average learning factor is calculated for each technology. 

The weights are based on the share of the initial cost estimate that is attributable to each component (Table 8.4). For 

technologies that do not share components, this weighted average learning rate is calculated exogenously, and input as a 

single component.

These technologies may still have a mix of revolutionary components and more mature components, but it is not necessary 

to include this detail in the model unless capacity from multiple technologies would contribute to the component learning. 

In the case of the solar PV technology, it is assumed that the module component accounts for 50% of the cost, and that the 

balance of system components accounts for the remaining 50%. Because the amount of end-use PV capacity (existing and 

projected) is significant relative to total solar PV capacity, and because the technology of the module component is common 

across the end-use and electric power sectors, the calculation of the learning factor for the PV module component also takes 

into account capacity built in the residential and commercial sectors.

Table 8.5 shows the capacity credit toward component learning for the various technologies. It was assumed that for all 

combined-cycle technologies, the turbine unit contributed two-thirds of the capacity, and the steam unit one-third. Therefore, 

building one gigawatt of gas combined cycle would contribute 0.67 gigawatts (GW) toward turbine learning, and 0.33 GW 

toward steam learning. Components that do not contribute to the capacity of the plant, such as the balance of plant category, 

receive 100% capacity credit for any capacity built with that component. For example, when calculating capacity for the 

“Balance of plant - CC” component, all combined cycle capacity would be counted 100%, both conventional and advanced.

Table 8.4. Component cost weights for new technologies

Technology

Pulverized 

Coal

Combustion

Turbineconventional

Combustion

Turbineadvanced HRSG Gasifier

Carbon

Capture/

Sequestration

Balance

of PlantIGCC

Balance 

of

PlantTurbine

Balance 

of

PlantCombined

Cycle

Fuel 

Prep

Biomass

Integrated

Coal-Gasification 

Comb Cycle (IGCC) 0% 0% 15% 20% 41% 0% 24% 0% 0% 0%

IGCCwith carbon 

sequestration 0% 0% 10% 15% 30% 30% 15% 0% 0% 0%

Conv Gas/Oil Comb 

Cycle 0% 30% 0% 40% 0% 0% 0% 0% 30% 0%

Adv Gas/Oil Comb 

Cycle (CC) 0% 0% 30% 40% 0% 0% 0% 0% 30% 0%

Adv CC with carbon 

sequestration 0% 0% 20% 25% 0% 40% 0% 0% 15% 0%

Conv Comb Turbine 0% 50% 0% 0% 0% 0% 0% 50% 0% 0%

Adv Comb Turbine 0% 0% 50% 0% 0% 0% 0% 50% 0% 0%

Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 50%

Note: All unlisted technologies have a 100% weight with the corresponding component. Components are not broken out for all technologies unless there 

is overlap with other technologies.

HRSG = Heat Recovery Steam Generator.

Source: Market-Based Advanced Coal Power Systems, May 1999, DOE/FE-0400.

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Table 8.5. Component capacity weights for new technologies

Technology

Pulverized 

Coal

Combustion

Turbineconventional

Combustion

Turbineadvanced HRSG Gasifier

Carbon

Capture/

Sequestration

Balance

of PlantIGCC

Balance 

of PlantTurbine

Balance of

PlantCombined

Cycle

Fuel 

Prep

Biomass

Integrated

Coal-Gasification Comb 

Cycle (IGCC) 0% 0% 67% 33% 100% 0% 100% 0% 0% 0%

IGCC with Carbon 

sequestration 0% 0% 67% 33% 100% 100% 100% 0% 0% 0%

Conv Gas/Oil Comb Cycle 0% 67% 0% 33% 0% 0% 0% 0% 100% 0%

Adv Gas/Oil Comb Cycle 

(CC) 0% 0% 67% 33% 0% 0% 0% 0% 100% 0%

Adv CC with carbon 

sequestration 0% 0% 67% 33% 0% 100% 0% 0% 100% 0%

Conv Comb Turbine 0% 100% 0% 0% 0% 0% 0% 100% 0% 0%

Adv Comb Turbine 0% 0% 100% 0% 0% 0% 0% 100% 0% 0%

Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 100%

HRSG = Heat Recovery Steam Generator.

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis.

Distributed generation 

Distributed generation is modeled in the end-use sectors (as described in the appropriate chapters) as well as in the EMM. 

This section describes the representation of distributed generation in the EMM only. Two generic distributed technologies are 

modeled. The first technology represents peaking capacity (capacity that has relatively high operating costs and is operated 

when demand levels are at their highest). The second generic technology for distributed generation represents base load capacity 

(capacity that is operated on a continuous basis under a variety of demand levels). See Table 8.2 for costs and performance 

assumptions. It is assumed that these plants reduce the costs of transmission upgrades that would otherwise be needed. 

Demand storage 

The EMM includes the option to build a new demand storage technology to simulate load shifting, through programs such as 

smart meters. This is modeled as a new technology build, but with operating characteristics similar to pumped storage. The 

technology is able to decrease the load in peak slices, but must generate to replace that demand in other time slices. There is an 

input factor that identifies the amount of replacement generation needed, where a factor of less than 1.0 can be used to represent 

peak shaving rather than purely shifting the load to other time periods. This plant type is limited to operating only in the peak load 

slices, and for AEO2014, it is assumed that this capacity is limited to 3.5% of peak demand on average in 2040, with limits varying 

from 2.2% to 6.8% of peak across the regions.

Representation of electricity demand 

The annual electricity demand projections from the NEMS demand modules are converted into load duration curves for each 

of the EMM regions (based on North American Electric Reliability Corporation regions and subregions) using historical hourly 

load data. The load duration curve in the EMM is made up of 9 time slices. First, the load data is split into three seasons (winter - 

December through March, summer - June through September, and fall/spring). Within each season the load data is sorted from 

high to low, and three load segments are created - a peak segment representing the top 1% of the load, and then two off-peak 

segments representing the next 49% and 50%, respectively. The seasons were defined to account for seasonal variation in supply 

availability.

Reserve margins—the percentage of capacity in excess of peak demand required to adequately maintain reliability during 

unforeseeable outages—are established for each region by its governing body – public utility commission, NERC region or 

Independent System Operators (ISOs)/Regional Transmission Operators (RTOs). The reserve margin values from the AEO2014

Reference case are set based on these regional Reference Margins reported to NERC and range from 14% to 17% [2].

Operating reserves

In addition to the planning reserve margin requirement, system operators typically require a specific level of operating reserves – 

generators available within a short period of time to meet demand in case a generator goes down or there is another disruption to 

supply. These reserves can be provided through plants that are already operating but not at full capacity (spinning reserves) 

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as well as through capacity not currently operating but that can be brought online quickly (non-spinning reserves). This is 

particularly important as more intermittent generators are added to the grid, because technologies like wind and solar have 

uncertain availability that can be difficult to predict. For AEO2014, the capacity and dispatch submodules of the EMM were 

both updated to include explicit constraints requiring spinning reserves in each load slice. The amount of spinning reserves 

required is computed as a percentage of the load height of the slice plus a percentage of the distance between the load of the 

slice and the seasonal peak. An additional requirement is calculated that is a percentage of the intermittent capacity available 

in that time period to reflect the greater uncertainty associated with the availability of intermittent resources. All technologies 

except for storage, intermittents and distributed generation can be used to meet spinning reserves. Different operating modes 

are developed for each technology type to allow the model to choose between operating a plant to maximize generation versus 

contributing to spinning reserves, or a combination of both. Minimum levels of generation are required if a plant is contributing to 

spinning reserves, and vary by plant type, with plant types typically associated with baseload operation having higher minimums 

than those that can more operate more flexibly to meet intermediate or peak demand.

Fossil fuel-fired and nuclear steam plant retirement 

Fossil-fired steam plant retirements and nuclear retirements are calculated endogenously within the model. Generating units 

are assumed to retire when it is no longer economical to continue running them. Each year, the model determines whether 

the market price of electricity is sufficient to support the continued operation of existing plant generators. A generating unit is 

assumed to retire if the expected revenues from the generator are not sufficient to cover the annual going-forward costs and if 

the overall cost of producing electricity can be lowered by building new replacement capacity. The going-forward costs include 

fuel, operations and maintenance costs and annual capital additions, which are unit-specific and based on historical data. The 

average capital additions for existing plants are $8 per kilowatt (kW) for oil and gas steam plants, $17 per kW for coal plants 

and $22 per kW for nuclear plants (in 2012 dollars). These costs are added to the estimated costs at existing plants regardless 

of their age. Beyond 30 years of age an additional $7 per kW capital charge for fossil plants and $33 per kW charge for nuclear 

plants is included in the retirement decision to reflect further investment to address the impacts of aging. Age-related cost 

increases are attributed to capital expenditures for major repairs or retrofits, decreases in plant performance, and/or increases in 

maintenance costs to mitigate the effects of aging.

EIA assumes all retirements reported as planned during the next ten years on the Form EIA-860 will occur. Additionally, the 

AEO2014 nuclear projection assumes a decrease of 5.7 GW by 2020 in several regions where existing nuclear units appear at 

risk of early closure due to a combination of high operating costs and low electricity prices.

Biomass co-firing

Coal-fired power plants are assumed to co-fire with biomass fuel if it is economical. Co-firing requires a capital investment for 

boiler modifications and fuel handling. This expenditure is assumed to be $285 per kW of biomass capacity. A coal-fired unit 

modified to allow co-firing can generate up to 15% of the total output using biomass fuel, assuming sufficient residue supplies 

are available.

Nuclear uprates

The AEO2014 nuclear power projection assumes capacity increases at existing units. Nuclear plant operators can increase the 

rated capacity at plants through power uprates, which are license amendments that must be approved by the U.S. Nuclear 

Regulatory Commission (NRC). Uprates can vary from small (less than 2%) increases in capacity, which require very little 

capital investment or plant modification, to extended uprates of 15-20%, requiring significant modifications. Recently, several 

companies have canceled previously planned extended uprates due to lower demand projections and low electricity prices 

[3]. AEO2014 assumes that only those uprates reported to EIA as planned modifications on the Form EIA-860 will take place 

in the Reference case, representing 0.7 GW of additional capacity. In the High Nuclear case (discussed in more detail later in 

this chapter), it is assumed that most plants with remaining uprate potential will implement uprates, with a total of 6.0 GW 

throughout the projection.

Interregional electricity trade

Both firm and economy electricity transactions among utilities in different regions are represented within the EMM. In general, 

firm power transactions involve the trading of capacity and energy to help another region satisfy its reserve margin requirement, 

while economy transactions involve energy transactions motivated by the marginal generation costs of different regions. The 

flow of power from region to region is constrained by the existing and planned capacity limits as reported in the NERC and 

Western Electricity Coordinating Council Summer and Winter Assessment of Reliability of Bulk Electricity Supply in North 

America, as well as information obtained from the Open Access Same-Time Information System (OASIS). Known firm power 

contracts are compiled from NERC’s Electricity Supply and Demand Database as well as information provided in the 2013 

Summer and Winter Assessments and individual ISO reports. They are locked in for the term of the contract. Contracts that are

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scheduled to expire by 2018 are assumed not to be renewed. Because there is no information available about expiration 

dates for contracts that go beyond 2018, they are assumed to be phased out linearly over 10 years. The EMM includes an 

option to add interregional transmission capacity. In some cases it may be more economical to build generating capacity in 

a neighboring region, but additional costs to expand the transmission grid will be incurred as well. Explicitly expanding the 

interregional transmission capacity may also make the transmission line available for additional economy trade.

Economy transactions are determined in the dispatching submodule by comparing the marginal generating costs of 

adjacent regions in each time slice. If one region has less expensive generating resources available in a given time period 

(adjusting for transmission losses and transmission capacity limits) than another region, the regions are assumed to 

exchange power.

International electricity trade

Two components of international firm power trade are represented in the EMM—existing and planned transactions, 

and unplanned transactions. Data on existing and planned transactions are compiled from NERC’s Electricity Supply 

and Demand Database and Canada’s National Energy Board. Unplanned firm power trade is represented by competing 

Canadian supply with U.S. domestic supply options. Canadian supply is represented via supply curves using cost data 

from the Department of Energy report, “Northern Lights: The Economic and Practical Potential of Imported Power from 

Canada” (DOE/PE-0079). International economy trade is determined endogenously based on surplus energy expected to 

be available from Canada by region in each time slice. Canadian surplus energy was determined using Canadian electricity 

supply and demand projections from the MAPLE-C model developed for Natural Resources Canada.

Electricity pricing

Electricity pricing is projected for 22 electricity market regions in AEO2014 for fully competitive, partially competitive and 

fully regulated supply regions. The price of electricity to the consumer comprises the price of generation, transmission, 

and distribution, including applicable taxes. Transmission and distribution are considered to remain regulated in the AEO; 

that is, the price of transmission and distribution is based on the average cost to build, operate and maintain these systems 

using a cost of service regulation model. The price of electricity in the regulated regions consists of the average cost of 

generation, transmission, and distribution for each customer class. In the competitive regions, the energy component 

of price is based on marginal cost, which is defined as the cost of the last (or most expensive) unit dispatched. The 

competitive generation price includes the marginal cost (fuel and variable operations and maintenance costs), taxes, and 

a capacity payment. The capacity payment is calculated as a combination of levelized costs for combustion turbines and 

the marginal value of capacity calculated within the EMM. The capacity payment is calculated for all competitive regions 

and should be viewed as a proxy for additional capital recovery that must be procured from customers rather than the 

representation of a specific market. The capacity payment also includes the costs associated with meeting the spinning 

reserves requirement discussed earlier. The total cost for meeting both constraints in a given region is calculated within 

the EMM, and allocated to the sectors based on their contribution to overall peak demand. The price of electricity in the 

regions with a competitive generation market consists of the competitive cost of generation summed with the average 

costs of transmission and distribution. The price for mixed regions reflects a load-weighted average of the competitive 

price and the regulated price, based on the percent of electricity load in the region subject to deregulation. In competitively 

supplied regions, a transition period is assumed to occur (usually over a 10-year period) from the effective date of 

restructuring, with a gradual shift to marginal cost pricing.

The Reference case assumes a transition to full competitive pricing in the three New York regions and in the ReliabilityFirst 

Corporation/East region, and a 97% transition to competitive pricing in New England (Vermont being the only 

fully-regulated state in that region). Six regions fully regulate their electricity supply, including the Florida Reliability 

Coordinating Council, three of the SERC Reliability Corporation subregions - Southeastern (SRSE), Central (SRCE) and 

Virginia-Carolina (SRVC) - Southwest Power Pool Regional Entity/North (SPNO), and the Western Electricity Coordinating 

Council/Rockies (RMPA). The Texas Reliability Entity, which in the past was considered fully competitive by 2010, is 

now only 88% competitive, since many cooperatives have declined to become competitive or allow competitive energy 

to be sold to their customers. California returned to almost fully regulated pricing in 2002, after beginning a transition 

to competition in 1998, with only 7% competitive supply sold currently in the Western Electricity Coordinating Council 

(WECC)/California region. All other regions reflect a mix of both competitive and regulated prices.

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There have been ongoing changes to pricing structures for ratepayers in competitive states since the inception of retail 

competition. The AEO has incorporated these changes as they have been incorporated into utility tariffs. These have included 

transition period rate reductions and freezes instituted by various states, and surcharges in California relating to the 2000-

2001 energy crisis in the state. Since price freezes for most customers have ended or will end in the next year or two, a 

large survey of utility tariffs found that many costs related to the transition to competition were now explicitly added to the 

distribution portion and sometimes the transmission portion of the customer bill, regardless of whether or not the customer 

bought generation service from a competitive or regulated supplier. There are some unexpected costs relating to unforeseen 

events. For instance, as a result of volatile fuel markets, state regulators have had a hard time enticing retail suppliers to offer 

competitive supply to residential and smaller commercial and industrial customers. They have often resorted to procuring the 

energy themselves through auction or competitive bids, or have allowed distribution utilities to procure the energy on the open 

market for their customers for a fee.

For AEO2014, typical charges that all customers must pay on the distribution portion of their bill (depending on where they 

reside) include: transition charges (including persistent stranded costs), public benefits charges (usually for efficiency and 

renewable energy programs), administrative costs of energy procurement, and nuclear decommissioning costs. Costs added to 

the transmission portion of the bill include the Federally Mandated Congestion Charges (FMCC), a bill pass-through associated 

with the Federal Energy Regulatory Commission passage of Standard Market Design (SMD) to enhance reliability of the 

transmission grid and control congestion. Additional costs not included in historical data sets have been added in adjustment 

factors to the transmission and distribution operations and maintenance costs, which impact the cost of both competitive and 

regulated electricity supply. Since most of these costs, such as transition costs, are temporary in nature, they are gradually 

phased out throughout the projection. Regions found to have these added costs include the Northeast Power Coordinating 

Council/New England and New York regions, the ReliabilityFirst Corporation/East and West regions, and the WECC/California 

region.

Fuel price expectations 

Capacity planning decisions in the EMM are based on a life cycle cost analysis over a 30-year period. This requires foresight 

assumptions for fuel prices. Expected prices for coal, natural gas and oil are derived using rational expectations, or ‘perfect 

foresight.’ In this approach, expectations for future years are defined by the realized solution values for these years in a prior 

run. The expectations for the world oil price and natural gas wellhead price are set using the resulting prices from a prior run. 

The markups to the delivered fuel prices are calculated based on the markups from the previous year within a NEMS run. Coal 

prices are determined using the same coal supply curves developed in the Coal Market Module. The supply curves produce 

prices at different levels of coal production, as a function of labor productivity, and costs and utilization of mines. Expectations 

for each supply curve are developed in the EMM based on the actual demand changes from the prior run throughout the 

projection horizon, resulting in updated mining utilization and different supply curves.

The perfect foresight approach generates an internally consistent scenario for which the formation of expectations is consistent 

with the projections realized in the model. The NEMS model involves iterative cycling of runs until the expected values and 

realized values for variables converge between cycles.

Nuclear fuel prices

Nuclear fuel prices are calculated through an offline analysis which determines the delivered price to generators in mills per 

kilowatthour. To produce reactor-grade uranium, the uranium (U308) must first be mined, and then sent through a conversion 

process to prepare for enrichment. The enrichment process takes the fuel to a given purity of U-235, typically 3-5% for 

commercial reactors in the United States. Finally, the fabrication process prepares the enriched uranium for use in a specific 

type of reactor core. The price of each of the processes is determined, and the prices are summed to get the final price of the 

delivered fuel. The one mill per kilowatthour charge that is assessed on nuclear generation to go to DOE’s Nuclear Waste Fund 

is also included in the final nuclear price. The analysis uses forecasts from Energy Resources International for the underlying 

uranium prices.

Legislation and regulations

Clean Air Act Amendments of 1990 (CAAA90) and Clean Air Interstate Rule (CAIR)

Currently, regulation of SO2 and NOX emissions is administered under the Clean Air Interstate Rule (CAIR), and AEO2014 

assumes that CAIR remains a binding regulation throughout the projection period. CAIR was initially promulgated in 2005, but 

has been challenged in court several times. The Cross-State Air Pollution Rule (CSAPR) was released by EPA in July 2011 and 

was intended to replace CAIR, but it was vacated by the U.S. Court of Appeals for the District of Columbia Circuit, and CAIR 

was reinstated.

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CAIR covers all fossil-fueled power plants greater than 25 megawatts in 27 states and the District of Columbia. There are annual 

emissions caps for SO2 and NOX and different states fall under each cap, as shown in the map in Figure 7, although all are in the 

eastern half of the United States. The caps for SO2 and NOX were set to allow states to achieve their National Ambient Air Quality 

Standards (NAAQS) for particulate matter (impacted by SO2 levels) and ground level ozone (impacted by NOX). Allowances can 

be traded among all participants in the CAAA90 Title IV program, not just those in CAIR states; however allowances are traded at 

a discount in non-CAIR states. AEO2014 represents emissions trading in both the CAIR and non-CAIR regions, as specified by the 

regulation, and includes banking of allowances consistent with CAIR’s provisions.

As specified in CAAA90, EPA developed a two-phase nitrogen oxide (NOx) program, with the first set of standards for existing 

coal plants applied in 1996 while the second set was implemented in 2000. Dry bottom wall-fired, and tangential-fired boilers, 

the most common boiler types, are referred to as Group 1 Boilers, and were required to make significant reductions beginning 

in 1996 and further reductions in 2000. Relative to their uncontrolled emission rates, which range roughly between 0.6 and 

1.0 pounds per million Btu, they are required to make reductions between 25 and 50% to meet the Phase I limits and further 

reductions to meet the Phase II limits. The EPA did not impose limits on existing oil and gas plants, but some states have 

instituted additional NOx regulations. All new fossil units are required to meet current standards. In pounds per million Btu, these 

limits are 0.11 for conventional coal, 0.02 for advanced coal, 0.02 for combined cycle, and 0.08 for combustion turbines. These 

NOx limits are incorporated in EMM.

Table 8.6 shows the average capital costs for environmental control equipment utilized by NEMS for existing coal plants as 

retrofit options in order to remove sulfur dioxide (SO2), nitrogen oxides (NOx), mercury and/or hydrogen chloride (HCl). In the 

EMM, plant-specific costs are calculated based on the size of the unit and other operating characteristics. The table reflects the 

capacity-weighted averages of all plants falling into each size category. FGD units are assumed to remove 95% of the SO2, while 

SCR units are assumed to remove 90% of the NOx. The EMM also includes an option to install a dry sorbent injection (DSI) 

system, which is assumed to remove 70% of the SO2. However, the DSI option is only available under the mercury and air toxics 

rule discussed in the next section, as its primary benefit is for reducing hydrogen chloride (HCl).

Figure 7. States covered by the Clean Air Interstate Rule

Source: U.S. Environmental Protection Agency, Clean Air Interstate Rule—Where You Live (Washington, DC, July 31, 2012), 

website http://www.epa.gov/cair/where.html.

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Mercury regulation

The Mercury and Air Toxics Standards (MATS) were finalized in December 2011 to fulfill EPA’s requirement to regulate 

mercury emissions from power plants. MATS also regulates other hazardous air pollutants (HAPS) such as hydrogen chloride 

(HCl) and fine particulate matter (PM2.5). MATS applies to coal- and oil-fired power plants with a nameplate capacity 

greater than 25 megawatts. The standards are scheduled to take effect in 2015, but allow for a one-year waiver to comply, 

and require that all qualifying units achieve the maximum achievable control technology (MACT) for each of the three 

covered pollutants. For AEO2014, EIA assumes that all coal-fired generating units with a capacity greater than 25 megawatts 

will comply with the rule beginning in 2016, due to the large number of plants requesting the one-year extension. All power 

plants are required to reduce their mercury emissions to 90% below their uncontrolled emissions levels.

Because the EMM does not explicitly model HCl or PM2.5, specific control technologies are assumed to be used to achieve 

compliance. In order to meet the HCl requirement, units must have either flue gas desulfurization (FGD) scrubbers or dry 

sorbent injection (DSI) systems in order to continue operating. A full fabric filter (FF) is also required to meet the PM2.5 

limits and to improve the effectiveness of the DSI technology. When plants alter their configuration by adding equipment 

such as an SCR to remove NOx or an SO2 scrubber, removal of mercury is often a resulting cobenefit. The EMM considers 

all combinations of controls and may choose to add NOX or SO2 controls purely to lower mercury if it is economic to do so. 

Plants can also add activated carbon injection systems specifically designed to remove mercury. Activated carbon can be 

injected in front of existing particulate control devices or a supplemental fabric filter can be added with activated carbon 

injection capability.

The equipment to inject activated carbon in front of an existing particulate control device is assumed to cost approximately 

$6 (2012 dollars) per kilowatt of capacity [4]. The costs of a supplemental fabric filter with activated carbon injection (often 

referred as a COPAC unit) are calculated by unit, with average costs shown in Table 8.6. The amount of activated carbon 

required to meet a given percentage removal target is given by the following equations [5].

For a unit with a cold side electrostatic precipitator (CSE), using subbituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 65 - (65.286 / (ACI + 1.026))

For a unit with a CSE, using bituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 100 - (469.379 / (ACI + 7.169))

For a unit with a CSE, and a supplemental fabric filter with activated carbon injection:

• Hg Removal (%) = 100 - (28.049 / (ACI + 0.428))

For a unit with a hot side electrostatic precipitator (HSE) or other particulate control, and a supplemental fabric filter with 

activated carbon injection:

• Hg Removal (%) = 100 - (43.068 / (ACI + 0.421))

ACI = activated carbon injection rate in pounds per million actual cubic feet of flue gas.

Table 8.6. Coal plant retrofit costs

2012 dollars per kW

Coal Plant Size (MW)

FGD Capital Costs ($/

kW)

SCR Capital Costs ($/

kW)

DSI Capital Costs ($/

kW)

FF Capital 

Costs

<100 896 417 189 258

100 - 299 635 270 94 192

300 - 499 502 217 50 163

500 - 699 444 200 37 147

>=700 399 183 31 135

Documentation for EPA Base Case v4.10 using the Integrated Planning Model, August 2010, EPA Contract EP-W-08-018, Appendices to 

Chapter 5.

Power plant mercury emissions assumptions

The EMM represents 35 coal plant configurations and assigns a mercury emissions modification factor (EMF) to each 

configuration. Each configuration represents different combinations of boiler types, particulate control devices, sulfur dioxide 

(SO2) control devices, nitrogen oxide (NOx) control devices, and mercury control devices. An EMF represents the amount of 

mercury that was in the fuel that remains after passing through all the plant’s systems. For example, an EMF of 0.60 means 

that 40% of the mercury that was in the fuel is removed by various parts of the plant. Table 8.7 provides the assumed EMFs 

for existing coal plant configurations without mercury-specific controls.

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2014 105
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Table 8.7. Mercury emission modification factors

Configuration EIA EMFs EPA EMFs

SO2 Control Particulate Control

NOx

Control Bit Coal Sub Coal Lignite Coal Bit Coal Sub Coal Lignite Coal

None BH -- 0.11 0.27 0.27 0.11 0.26 1.00

Wet BH None 0.05 0.27 0.27 0.03 0.27 1.00

Wet BH SCR 0.10 0.27 0.27 0.10 0.15 0.56

Dry BH -- 0.05 0.75 0.75 0.50 0.75 1.00

None CSE -- 0.64 0.97 0.97 0.64 0.97 1.00

Wet CSE None 0.34 0.73 0.73 0.34 0.84 0.56

Wet CSE SCR 0.10 0.73 0.73 0.10 0.34 0.56

Dry CSE -- 0.64 0.65 0.65 0.64 0.65 1.00

None HSE/Oth -- 0.90 0.94 0.94 0.90 0.94 1.00

Wet HSE/Oth None 0.58 0.80 0.80 0.58 0.80 1.00

Wet HSE/Oth SCR 0.42 0.76 0.76 0.10 0.75 1.00

Dry HSE/Oth -- 0.60 0.85 0.85 0.60 0.85 1.00

Notes: SO2 Controls - Wet = Wet Scrubber and Dry = Dry Scrubber, Particulate Controls, BH - fabric filter/baghouse. CSE = cold side electrostatic 

precipitator, HSE = hot side electrostatic precipitator, NOx Controls, SCR = selective catalytic reduction, 

— = not applicable, Bit = bituminous coal, Sub = subbituminous coal. The NOx control system is not assumed to enhance mercury removal unless a wet 

scrubber is present, so it is left blank in such configurations. Sources: EPA, EMFs. www.epa.gov/clearskies/technical.html. EIA EMFs not from EPA: Lignite 

EMFs, Mercury Control Technologies for Coal-Fired Power Plants, presented by the Office of Fossil Energy on July 8, 2003. Bituminous coal mercury removal 

for a Wet/HSE/Oth/SCR configured plant, Table EMF1, Analysis of Mercury Control Cost and Performance, Office of Fossil Energy & National Energy 

Technology Laboratory, U.S. Department of Energy, January 2003, Washington, DC.

Planned SO2 Scrubber and NOx control equipment additions

EIA assumes that all planned retrofits, as reported on the Form EIA-860, will occur as currently scheduled. For AEO2014, this 

includes 16.9 GW of planned SO2 scrubbers (Table 8.8) and 10.2 GW of planned selective catalytic reduction (SCR).

Carbon capture and sequestration retrofits

Although a federal greenhouse gas program is not assumed in the AEO2014 Reference case, the EMM includes the option of 

retrofitting existing coal plants for carbon capture and sequestration (CCS). This option is important when considering alternate 

scenarios that do constrain carbon emissions. The modeling structure for CCS retrofits within the EMM was developed by the 

National Energy Technology Laboratory[6] and uses a generic model of retrofit costs as a function of basic plant characteristics 

(such as heatrate). The costs have been adjusted to be consistent with costs of new CCS technologies. The CCS retrofits are 

assumed to remove 90% of the carbon input. The addition of the CCS equipment results in a capacity derate of around 30% and 

reduced efficiency of 43% at the existing coal plant. The costs depend on the size and efficiency of the plant, with the capital 

costs averaging $1,635 per kilowatt, and ranging from $1,193 to $2,255 per kilowatt. It was assumed that only plants greater than 

500 megawatts and with heat rates below 12,000 Btu per kilowatthour would be considered for CCS retrofits.

State air emissions regulation

AEO2014 continues to model the Northeast Regional Greenhouse Gas Initiative (RGGI), which applies to fossil-fuel powered 

plants over 25 megawatts in the Northeastern United States. The State of New Jersey withdrew from the program at the 

end of 2011, leaving nine states in the accord. The rule caps CO2 emissions from covered electricity generating facilities and 

requires that they account for each ton of CO2 emitted with an allowance purchased at auction. Because the baseline and 

projected emissions were calculated before the economic recession that began in 2008, the actual emissions in the first years 

of the program have been less than the cap, leading to excess allowances and allowance prices at the floor price. As a result, 

in February 2013 program officials announced a tightening of the cap starting in 2014. AEO2014 applies these revised targets, 

which reflect a cap that is 45% of the original target for 2014.

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The California Assembly Bill 32 (AB 32), the Global Warming Solutions Act of 2006, authorized the California Air Resources 

Board (CARB) to set California’s GHG reduction goals for 2020 and establish a comprehensive, multi-year program to reduce 

GHG emissions in California. As one of the major initiatives for AB 32, CARB designed a cap-and-trade program that started 

on January 1, 2012, with the enforceable compliance obligations beginning in 2013 for the electric power sector and industrial 

facilities. Fuel providers must comply starting in 2015. The AB32 cap-and-trade provisions are incorporated in AEO2014 through 

an emission constraint in the EMM that also accounts for the emissions determined by the other sectors. Within the power sector, 

emissions from plants owned by California utilities but located out of state as well as emissions from electricity imports into 

California count toward the emission cap, and estimates of these emissions are included in the EMM constraint. An allowance 

price is calculated and added to fuel prices for the affected sectors. Limited banking and borrowing of allowances as well as 

an allowance reserve and offsets have been modeled, as specified in the Bill, providing some compliance flexibility and cost 

containment.

Table 8.8. Planned SO2 scrubber additions by EMM region

Gigawatts

Texas Reliability Entity 0.0

Florida Reliability Coordinating Council 0.0

Midwest Reliability Council - East 1.5

Midwest Reliability Council - West 2.2

Northeast Power Coordinating Council/New England 0.0

Northeast Power Coordinating Council/NYC-Westchester 0.0

Northeast Power Coordinating Council/Long Island 0.0

Northeast Power Coordinating Council/Upstate 0.0

ReliabilityFirst Corporation/East 0.0

ReliabilityFirst Corporation/Michigan 2.8

ReliabilityFirst Corporation/West 3.7

SERC Reliability Corporation/Delta 0.0

SERC Reliability Corporation/Gateway 2.2

SERC Reliability Corporation/Southeastern 3.6

SERC Reliability Corporation/Central 0.0

SERC Reliability Corporation/Virginia-Carolina 0.0

Southwest Power Pool/North 1.0

Southwest Power Pool/South 0.0

Western Electricity Coordinating Council/Southwest 0.0

Western Electricity Coordinating Council/California 0.0

Western Electricity Coordinating Council/Northwest Power Pool Area 0.0

Western Electricity Coordinating Council/Rockies 0.0

Total 16.9

Source: U.S. Energy Information Administration, Form EIA-860, “Annual Electric Generator Report.”

Energy Policy Acts of 1992 (EPACT92) and 2005 (EPACT05) 

The provisions of EPACT92 include revised licensing procedures for nuclear plants and the creation of exempt wholesale 

generators (EWGs). EPACT92 also implemented a permanent 10% investment tax credit for geothermal and solar facilities, 

and introduced a production tax credit for eligible renewable technologies (subsequently extended and expanded). EPACT05 

provides a 20% investment tax credit for Integrated Coal-Gasification Combined Cycle capacity and a 15% investment tax credit 

for other advanced coal technologies. These credits are limited to 3 GW in both cases. These credits have been fully allocated 

and are not assumed to be available for new, unplanned capacity built within the EMM. EPACT05 also contains a production tax 

credit (PTC) of 1.8 cents (nominal) per kWh for new nuclear capacity beginning operation by 2020. This PTC is specified for the 

first 8 years of operation, is limited to $125 million annually, and is limited to 6 GW of new capacity. However, this credit may be 

shared to additional units if more than 6 GW are under construction by January 1, 2014. EPACT05 extended the PTC for qualifying 

renewable facilities by 2 years, or December 31, 2007. It also repealed the Public Utility Holding Company Act (PUHCA).

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Energy Improvement and Extension Act 2008 (EIEA2008) 

EIEA2008 extended the investment tax credit of 30% through 2016 for solar and fuel cell facilities. After 2016, the tax credit for 

solar facilities reverts back to the 10% level set by EPACT92.

American Recovery and Reinvestment Act (ARRA) 

Updated tax credits for Renewables 

ARRA extended the expiration date for the PTC to January 1, 2013, for wind and January 1, 2014, for all other eligible renewable 

resources. In addition, ARRA allows companies to choose an investment tax credit (ITC) of 30% in lieu of the PTC and allows for 

a grant in lieu of this credit to be funded by the U.S. Treasury. For some technologies, such as wind, the full PTC would appear to 

be more valuable than the 30% ITC; however, the difference can be small. Qualitative factors, such as the lack of partners with 

sufficient tax liability, may cause companies to favor the ITC grant option. AEO2014 generally assumes that renewable electricity 

projects will claim the more favorable tax credit or grant option available to them.

Loan guarantees for renewables

ARRA provided $6 billion to pay the cost of guarantees for loans authorized by the Energy Policy Act of 2005. While most 

renewable projects which started construction prior to September 30, 2011 are potentially eligible for these loan guarantees, the 

application and approval of guarantees for specific projects is a highly discretionary process, and has thus far been limited. While 

AEO2014 includes projects that have received loan guarantees under this authority, it does not assume automatic award of the 

loans to potentially eligible technologies.

Support for CCS

ARRA provided $3.4 billion for additional research and development on fossil energy technologies. A portion of this funding 

is expected to be used to fund projects under the Clean Coal Power Initiative program, focusing on projects that capture and 

sequester greenhouse gases. To reflect the impact of this provision, AEO2014 Reference case assumes that an additional 1 GW of 

coal capacity with CCS will be stimulated by 2018.

Smart grid expenditures

ARRA provides $4.5 billion for smart grid demonstration projects. While somewhat difficult to define, smart grid technologies 

generally include a wide array of measurement, communications, and control equipment employed throughout the transmission 

and distribution system that will enable real-time monitoring of the production, flow, and use of power from the generator to the 

consumer. Among other things, these smart grid technologies are expected to enable more efficient use of the transmission and 

distribution grid, lower line losses, facilitate greater use of renewables, and provide information to utilities and their customers 

that will lead to greater investment in energy efficiency and reduced peak load demands. The funds provided will not fund a 

widespread implementation of smart grid technologies, but could stimulate more rapid investment than would otherwise occur.

Several changes were made throughout NEMS to represent the impacts of the smart grid funding provided in ARRA. In the 

electricity module, it was assumed that line losses would fall slightly, peak loads would fall as customers shifted their usage 

patterns, and customers would be more responsive to pricing signals. Historically, line losses, expressed as the percentage of 

electricity lost, have been falling for many years as utilities make investments to replace aging or failing equipment.

Smart grid technologies also have the potential to reduce peak demand through the increased deployment of demand response 

programs. In AEO2014, it is assumed that the Federal expenditures on smart grid technologies will stimulate efforts that reduce 

peak demand from what they otherwise would be, with the amount of total peak load reduction growing from 2.2% initially 

to 3.5% by 2040, although the shifts vary by region. Load is shifted to offpeak hours, so net energy consumed remains largely 

constant.

American Taxpayer Relief Act of 2012 (ATRA)

Passed in January 2012, the impacts of ATRA were included in a side case of AEO2013 and are now reflected in the Reference 

case of AEO2014. ATRA extended the expiration date of the wind production tax credit by one year, and redefined the criteria for 

all qualifying projects to be based on ‘under construction’ by December 31, 2013 rather than placed in service by that same date, 

effectively extending the credit for the length of the typical construction period.

FERC Orders 888 and 889 

FERC issued two related rules (Orders 888 and 889) designed to bring low-cost power to consumers through competition, ensure 

continued reliability in the industry, and provide for open and equitable transmission services by owners of these facilities. 

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Specifically, Order 888 requires open access to the transmission grid currently owned and operated by utilities. The transmission 

owners must file nondiscriminatory tariffs that offer other suppliers the same services that the owners provide for themselves.

Order 888 also allows these utilities to recover stranded costs (investments in generating assets that are unrecoverable due to 

consumers selecting another supplier). Order 889 requires utilities to implement standards of conduct and an Open Access SameTime Information System (OASIS) through which utilities and non-utilities can receive information regarding the transmission 

system. As a result, utilities have functionally or physically unbundled their marketing functions from their transmission functions.

These orders are represented in EMM by assuming that all generators in a given region are able to satisfy load requirements 

anywhere within the region. Similarly, it is assumed that transactions between regions will occur if the cost differentials between 

them make such transactions economical.

Electricity alternative cases 

Accelerated Retirement cases

For AEO2014, three alternate cases were run to examine the impacts of potentially large amounts of retirements of baseload coal 

and nuclear plants on the electric power sector. In recent years, a combination of low natural gas prices, high retrofit or repair 

costs and uncertain environmental legislation have led to an increase in announced retirements of coal and nuclear plants.

These scenarios are discussed in an Issues in Focus article in the full AEO2014 report.

• The Accelerated Nuclear Retirement case assumes that reactors will not receive a second license renewal, therefore all existing 

plants are retired within 60 years of operation. Non-fuel operating costs at existing nuclear plants are assumed to increase 

by 3% per year after 2013. The 4.8 GW of announced retirements remain as in the Reference case, along with the decrease 

of 5.7 GW of nuclear capacity by 2020 to reflect plants at risk of early closure in specific regions. In this case an additional 

37.4 GW of nuclear capacity is retired by 2040, relative to the Reference case. The Accelerated Nuclear Retirement case also 

assumes that no new nuclear capacity will be added throughout the projection, with the exception of capacity already under 

construction.

• The Accelerated Coal Retirement case includes the assumptions used for the High Coal Cost case, including lower productivity 

and higher costs associated with mining and transportation rates. (This case is described in more detail in the Coal chapter 

of this report). By 2040, delivered coal prices are more than 60% higher in the Accelerated Coal Retirement case than the 

Reference case. This case also assumes that non-fuel operating costs at existing coal plants increase by 3% per year after 2013.

• The Accelerated Coal and Nuclear Retirement case combines the assumptions of the Accelerated Coal Retirement and 

Accelerated Nuclear Retirement cases.

Nuclear Alternative cases

For AEO2014, two alternate cases were run for nuclear power plants to address uncertainties about the operating lives of existing 

reactors, the potential for new nuclear capacity, and capacity uprates at existing plants. 

• The Low Nuclear case combines the Accelerated Nuclear Retirement case with the High Oil and Gas Resource case and the 

No Sunset case. (All case descriptions can be found in Table 1.1 of this report). This combines more pessimistic assumptions 

regarding nuclear costs and lifetimes with more favorable conditions for natural gas-fired and renewable technologies, so that 

the impacts on the power sector can be viewed under an outlook where output from nuclear power is greatly reduced. 

• The High Nuclear case assumes that all existing nuclear units will receive a second license renewal and operate beyond 60 

years (excluding 4.8 GW of announced retirements). In the Reference case, beyond the announced retirements an additional 

decrease of 5.7 GW of nuclear capacity is assumed to be retired by 2020. The High Nuclear case was run to provide a more 

optimistic outlook where all licenses are renewed and all plants are assumed to find it economic to continue operating beyond 

60 years. The High Nuclear case also assumes additional planned nuclear capacity is completed based on combined license 

(COL) applications with the NRC and whether an Atomic Safety and Licensing Board hearing has been scheduled for a COL. 

The High Nuclear case assumes 12.6 GW of planned capacity additions, as compared with the 5.5 GW of planned capacity 

additions in the Reference case. Finally, the High Nuclear case assumes a total of 6.0 GW of uprates at existing plants, 

reflecting an assumption that most plants with remaining uprate potential will elect to perform such uprates.

Flat Electricity Demand case

For AEO2014, a case was developed combining technology and efficiency improvements across the end use demand sectors to 

create a case that projects retail sales to the grid to be relatively flat at current levels. This case was developed to analyze the 

impacts on the power sector capacity and generation requirements under an extreme scenario of no demand growth. The Flat 

Electricity Demand case uses the assumptions in the Best Available Technology case for the residential and commercial sectors. 

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Flat Electricity Demand case

For AEO2014, a case was developed combining technology and efficiency improvements across the end use demand sectors to 

create a case that projects retail sales to the grid to be relatively flat at current levels. This case was developed to analyze the 

impacts on the power sector capacity and generation requirements under an extreme scenario of no demand growth. The Flat 

Electricity Demand case uses the assumptions in the Best Available Technology case for the residential and commercial sectors. 

Notes and sources

[1] Review of Power Plant Cost and Performance Assumptions for NEMS, Science Applications International Corporation, April 

2013. 

[2] “Exelon Cancels Power Uprates for Lasalle, Limerick,” June 12, 2013, 

http://www.platts.com/latest-news/electric-power/washington/exelon-cancels-power-uprates-for-lasalle-limerick-21152061. 

[3] North American Electric Reliability Corporation, 2013 Summer Reliability Assessment (Atlanta, GA: May 2013), 

http://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/2013SRA_Final.pdf .

[4] These costs were developed using the National Energy Technology Laboratory Mercury Control Performance and Cost Model, 

1998.

[5] U.S. Department of Energy, Analysis of Mercury Control Cost and Performance, Office of Fossil Energy & National

Energy Technology Laboratory, January 2003.

[6] Retrofitting Coal-Fired Power Plants for Carbon Dioxide Capture and Sequestration - Exploratory Testing of NEMS for

Integrated Assessments, DOE/NETL-2008/1309, P.A. Geisbrecht, January 18, 2009.

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